DAG-Based Attack and Defense Modeling: Don't Miss the Forest for the Attack Trees
It provides a comprehensive overview for security practitioners to choose appropriate modeling techniques, but it is incremental as a survey.
This paper surveys over 30 directed acyclic graph (DAG)-based methodologies for attack and defense modeling in security, summarizing and comparing their features to propose a taxonomy and aid in technique selection.
This paper presents the current state of the art on attack and defense modeling approaches that are based on directed acyclic graphs (DAGs). DAGs allow for a hierarchical decomposition of complex scenarios into simple, easily understandable and quantifiable actions. Methods based on threat trees and Bayesian networks are two well-known approaches to security modeling. However there exist more than 30 DAG-based methodologies, each having different features and goals. The objective of this survey is to present a complete overview of graphical attack and defense modeling techniques based on DAGs. This consists of summarizing the existing methodologies, comparing their features and proposing a taxonomy of the described formalisms. This article also supports the selection of an adequate modeling technique depending on user requirements.